perf: cap chat output tokens via ollama_num_predict to bound reply latency

Spoken (TTS) replies are 1-2 sentences, so an unbounded num_predict only
exposes the worst case where the chat model rambles or loops. Add an
ollama_num_predict config (default 512, 0 disables) wired into the reply
loop's chat call on both the native- and text-tool paths. The 512-token
headroom stays well above this app's short tool-call JSON, so capping never
truncates a tool call. This keeps the user's quality model instead of
downgrading it. Configurable in the container via OLLAMA_NUM_PREDICT.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

docker/jarvis-config.template.json

@@ -4,6 +4,7 @@
   "ollama_base_url": "${OLLAMA_BASE_URL}",
   "ollama_embed_model": "${OLLAMA_EMBED_MODEL}",
   "ollama_chat_model": "${OLLAMA_CHAT_MODEL}",
+  "ollama_num_predict": "${OLLAMA_NUM_PREDICT}",
   "intent_judge_model": "${OLLAMA_INTENT_MODEL}",
   "tts_enabled": true,
   "tts_engine": "${TTS_ENGINE}",